We have developed a model using 37 dimeric aryl diketo acids to identify the physiochemical properties conducive for inhibition of HIV-1 integrase using genetic algorithms (GA). GA is a feature selection method based off of contemporary evolution theory in regards to the change and transference of genetic code from parents to child. GA is used to select a small subset of descriptors for QSAR modeling. Approximately 400 constitutional, geometrical, topological, electrostatic, and quantum-chemical descriptors were computed for each structure. Models generated using GA are ranked based on satisfying predictive statistical constraints (r2 > 0.6, r2validation > 0.5, r2test > 0.5). The top ranked models are considered for analysis to identify the physiochemical features of dimeric aryl diketo acids conducive for inhibition of HIV-1 integrase. Understanding these physiochemical features would lead to the development of novel compounds with greater inhibitory effects towards HIV-1 integrase.

Genetic algorithm modeling of dimeric aryl diketo acid inhibitors for HIV-1 integrase

243rd National Meeting (2012)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.